Contactless respiration monitoring using Doppler radar is an important technology for healthcare applications. The radar measures small displacements of the body surface. In this study, we propose a new algorithm to separate multiple targets placed closely together at the same range but at different lateral positions using ultra-wideband array radar and the Capon method. The Capon method, which is an adaptive beamforming - technique, assumes that arrival echoes are not correlated. However, echoes from the human body should be correlated and this reduces system performance. We improve the performance - by introducing two different diagonal loading factor values for direction of arrival estimation and weight vector calculation. In an experimental study, the proposed method separates the echoes from two patients spaced at a lateral distance of approximately 70 mm. The estimated displacement error when using the proposed method is less than 0.13 mm, while that of the conventional method is 2.7 mm.

Schema mappings play a central role in many data integration and data exchange scenarios. In those applications, users need to quickly and correctly specify how data represented in one format is converted into a different format. Clio (L. Popa et al., 2002) is a joint research project between IBM and the University of Toronto studying the creation, maintenance, and use of schema mappings. There have always been two goals in our work in Clio: 1) the automatic creation of logical assertions that capture the way one or more source schemas are mapped into a target schema, and 2) the generation of transformation queries or programs that transform a source data instance into a target data instance.

We introduce a network-based problem detection framework for distributed systems, which includes a data-mining method for discovering dynamic dependencies among distributed services from transaction data collected from network, and a novel problem detection method based on the discovered dependencies. From observed containments of transaction execution time periods, we estimate the probabilities of accidental and non-accidental containments, and build a competitive model for discovering direct dependencies by using a model estimation method based on the online EM algorithm. Utilizing the discovered dependency information, we also propose a hierarchical problem detection framework, where microscopic dependency information is incorporated with a macroscopic anomaly metric that monitors the behavior of the system as a whole. This feature is made possible by employing a network-based design which provides overall information of the system without any impact on the performance.

We consider the problem of finding a set of attribute values that give a high quality binary segmentation of a database. The quality of a segmentation is defined by an objective function suitable for the user's objective, such as "mean squared error," "mutual information," or "/spl chi//sup 2/" each of which is defined in terms of the distribution of a given target attribute. Our goal is to find value groups on a given conditional domain that split databases into two segments, optimizing the value of an objective function. Though the problem is intractable for general objective functions, there are feasible algorithms for finding high quality binary segmentations when the objective function is convex, and we prove that the typical criteria mentioned above are all convex. We propose two practical algorithms, based on computational geometry techniques, which find a much better value group than conventional heuristics.

We discuss data mining based on association rules for two numeric attributes and one Boolean attribute. For example, in a database of bank customers, Age and Balance are two numeric attributes, and CardLoan is a Boolean attribute. Taking the pair (Age, Balance) as a point in two-dimensional space, we consider an association rule of the form ((Age,Balance) ∈P)⇒(CardLoan = Yes), which implies that bank customers whose ages and balances fall within a planar region P tend to take out credit card loans with a high probability.We consider two classes of regions, rectangles and admissible (i.e., connected and x-monotone) regions. For each class, we propose efficient algorithms for computing the regions that give optimal association rules for gain, support, and confidence, respectively. We have implemented the algorithms for admissible regions as well as several advanced functions based on them in our data mining system named SONAR (System for Optimized Numeric Association Rules), where the rules are visualized by using a graphic user interface to make it easy for users to gain an intuitive understanding of rules.

Given a huge database, we address the problem of finding association rules for numeric attributes, such as Permission to make digital/hard copies of all or pati of this material for personal or claasroom usc is granted without fee provided that the copies are not made or distributed for pro~t or cornmesvial advantage, the copyright notice, the title of the publication and Its date appear, and notice is given that cop yright is by permission of the ACM, Inc.To copy otherwise, to repubtish, to post on servers or to redistribute to lists, requires specific permission and/or fee.PODS '96, Montreal Quebec Canada

We discuss data mining based on association rules for two numeric attributes and one Boolean attribute. For example, in a database of bank customers, "Age" and "Balance" are two numeric attributes, and "CardLoan" is a Boolean attribute. Taking the pair (Age, Balance) as a point in two-dimensional space, we consider an association rule of the form((Age, Balance) ∈ P) ⇒ (CardLoan = Yes),which implies that bank customers whose ages and balances fall in a planar region P tend to use card loan with a high probability. We consider two classes of regions, rectangles and admissible (i.e. connected and x-monotone) regions. For each class, we propose efficient algorithms for computing the regions that give optimal association rules for gain, support, and confidence, respectively. We have implemented the algorithms for admissible regions, and constructed a system for visualizing the rules.

No abstract available.